DeepSpaceDB: a spatial transcriptomics atlas for interactive in-depth analysis of tissues and tissue microenvironments.

Abstract

Spatial transcriptomics enables detailed mapping of gene expression within tissues, revealing spatial organization of cellular and molecular processes. However, generating such data is costly and technically challenging, and analysis requires advanced bioinformatics skills. Although public datasets are growing, existing databases offer limited tools for interactive exploration and cross-sample comparison. Here, we introduce DeepSpaceDB (www.deepspacedb.com), a next-generation spatial transcriptomics database designed to address these challenges. The current version of DeepSpaceDB focuses on 10X Genomics Visium samples, ensuring higher-quality analyses and enhanced tools. This distinguishes it from databases that prioritize broad platform coverage over functionality. Emphasizing interactivity and advanced analytics, DeepSpaceDB enables flexible exploration of spatial transcriptomics data. Users can interactively compare gene expression across regions within or between tissue slices, such as between hippocampal areas of an Alzheimer's model mouse and a control. The database also offers quality indicators, database-wide trends, and interactive visualizations like zoomable plots and hover-based info. Moreover, these functions are not restricted to samples in our database but can also be applied to samples uploaded by users. Combining advanced tools with interactive features, DeepSpaceDB is a powerful resource for spatial transcriptomics, enabling deeper insights into tissue organization and disease biology.